code: def test_video_mode(tmp_path: Path, frames_per_group: int):
      setup_dummy_dataset(tmp_path)
  
      ds = Vimeo90kSeptuplet(
          root=tmp_path,
          as_video=True,
          frames_per_group=frames_per_group,
          split="train",
          pil_transform=Compose([ToTensor(), lambda t: 2 * t]),
          tensor_transform=lambda t: 3 * t,
      )
  
      assert len(ds) == 2
  
      assert torch.allclose(
          ds[0],
          torch.ones(frames_per_group, 3, 10, 10)
          * torch.tensor(
              [10 + i for i in range(1, frames_per_group + 1)]
          ).view(-1, 1, 1, 1)
          * 6
          / 255,
      )
  
      assert torch.allclose(
          ds[1],
          torch.ones(frames_per_group, 3, 10, 10)
          * torch.tensor(
              [30 + i for i in range(1, frames_per_group + 1)]
          ).view(-1, 1, 1, 1)
          * 6
          / 255,
      )
  
file_path: NeuralCompression/tests/data/test_vimeo_90k_septuplet.py
imports: from pathlib import Path
  import numpy
  import pytest
  import torch
  from PIL import Image
  from torchvision.transforms import Compose, ToTensor
  from neuralcompression.data._vimeo_90k_septuplet import Vimeo90kSeptuplet
label_desc: Use image node_id 2 for calling a global function with example usage: test_video_mode(tmp_path, frames_per_group) without return types